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Derived Relational Responding and Horse Track Betting. Seth W. Whiting Mark R. Dixon. Gambling. The National Council of Problem Gambling suggested that upwards of 80 percent of American residents have gambled once or more in their life (2011).
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Derived Relational RespondingandHorse Track Betting Seth W. Whiting Mark R. Dixon
Gambling • The National Council of Problem Gambling suggested that upwards of 80 percent of American residents have gambled once or more in their life (2011). • Further, approximately 2.3 percent of the general population engage in problem gambling (Kessler et al., 2008).
Horse Racing • Consumer spent approximately $6.4 billion at racetrack casinos in 2009 • This reflects an increase of 5% since 2008 • As of 2010, there are 44 racetrack casinos throughout 12 states • (American Gaming Association) • (Dunstan, 1997) Casino Games Racetrack Facilities
Influences on Horse Gambling • Choices based on formal properties • Would you gamble on… Horse 1 Horse 2
Horses at the Kentucky Derby… • All look similar • Other features: names, colors, jockey colors
Transformation of Function • Transformation: in the absence of direct training, a stimulus can acquire a function through inclusion in a stimulus class or relation(Dougher, Perkins, Greenway, Koons, & Chiasson, 2002) • Rehfeldt & Hayes (1998) examined this phenomenon with untrained temporal differentiation
Rehfeldt & Hayes (1998) • Participants responded on a conjunc FR5 t ı < IRT < t₂ reinforcement schedule • Stimuli were placed in a class via conditional discrimination training • Participants clicked on novel stimuli with the same temporal responses, despite the lack of training • Responding can come under discriminative temporal control via transformation of function
Dixon, Wilson, & Whiting (in press) • Extended these findings to a horse track gambling context • Participants were trained to respond to stimuli on conjunc FR5 t ı < IRT < t₂ reinforcement schedule • When placed in an equivalence class with a colored square, participants increased bet allocation to horse of the color requiring clicking on the lowest IRT • No direct training
Dixon, Wilson, & Whiting (in press) • However, betting was between 8 colored horses, and only 3 were included in conditional discrimination training • Resulting in inconsistent changes • and some increases on “medium” and “slow” horse • Mastery on equivalence test was not required • Participants were inexperienced gamblers (SOGS 0-2)
Current Study • Seek to extend the previous studies by… • Examining the transformation of function on a simulated horse track • Using Problem/Pathological gamblers as participants • Controlled betting- 2 horses only • Require demonstration of equivalence relation
Participants and Setting • Participants included 3 undergraduate students from Southern Illinois University • Procedures completed on campus in a lab setting on a desktop computer • Simulated horse track was created using Microsoft Visual Studio 2008
Participants • Average age: 20.67 (20-21) • All Male, income <5000, single, no children • Mean SOGS score: 4.67 (4-6)
Horse Track Pre-Test • Participants bet up to 10 hypothetical credits per trial • This phase lasted for 10-30 trials, randomly selected by computer • Nonconcurrent multiple baseline • Random outcomes
Video of horse race • Notes: • Orange and purple horses were each programmed to win for sure on 30% of trials • 70% of trials had random outcome • All horses speed up or slow down several times • 1/8 chance to win- all horses pay 8X bet
Pretraining • One of two random stimuli was presented. Participants had to respond on an FR-5 schedule to earn reinforcement across 15 trials. • Stimuli were not used at any other time
Conjunc FR 5 t1 < IRT < t2 Training and Testing Conjunc FR 5 0.0 < IRT < 0.5 Conjunc FR 5 1.5 < IRT < 3.0 A1 A3
Conjunc FR 5 t1 < IRT < t2 Training and Testing • Participants were required to click on A1 and A3 stimuli for 15 successful trials each. • The stimuli were then presented randomly for 16 trials to test the trained functions. • 13/16 to pass
Match-to-Sample • A-B and B-C relations were trained individually and mixed. • Reflexivity A-A B-B C-C • Symmetry B-A C-B • Transitivity A-C • Equivalence C-A
A-B B-C Mixed A-B, B-C Refl. A-A, B-B, C-C Sym. B-A, C-B Trans. A-C Equiv. C-A Criterion: 16/18 Feedback: Yes
A-B B-C Mixed A-B, B-C Refl. A-A, B-B, C-C Sym. B-A, C-B Trans. A-C Equiv. C-A Criterion: 16/18 Feedback: Yes
A-B B-C Mixed A-B, B-C Refl. A-A, B-B, C-C Sym. B-A, C-B Trans. A-C Equiv. C-A Criterion: 32/36 Feedback: Yes
A-B B-C Mixed A-B, B-C Refl. A-A, B-B, C-C Sym. B-A, C-B Trans. A-C Equiv. C-A Criterion: none Feedback: no
A-B B-C Mixed A-B, B-C Refl. A-A, B-B, C-C Sym. B-A, C-B Trans. A-C Equiv. C-A Criterion: none Feedback: no
A-B B-C Mixed A-B, B-C Refl. A-A, B-B, C-C Sym. B-A, C-B Trans. A-C Equiv. C-A Criterion: none Feedback: no
A-B B-C Mixed A-B, B-C Refl. A-A, B-B, C-C Sym. B-A, C-B Trans. A-C Equiv. C-A Criterion: 15/18 Feedback: No If failed: back to Mixed
Horse Track Post-Test • Betting was again measured over 31-60 trials on the horse track • Number of trials was again selected at random
Results *Participant 2 failed equivalence testing once, participant 3 failed twice. Testing scores reflect the percent correct when criterion was met
Results • All participants passed temporal testing in 1-2 trial blocks • Participants 2 and 3 failed equivalence testing, but finished with 100% accuracy when they met criterion
Betting Summary +8.46% +0.93% +17.66%
Betting Results • All participants increased betting on the “fast” horse • Participant 2 changed bets minimally • Reported that the odds were likely even
Discussion • Results were consistent • Change maintained throughout all trials following training • Scores on equivalence test showed the presence of established equivalence classes and derived relations • Post-training gambling allocation suggests that the color of the horse with formal similarity to the C stimuli in relational training acquired the function of “faster than”
Discussion • Arbitrary stimuli acquired functions through differential reinforcement, and those functions transformed to other stimuli placed in the same class • The results provide evidence that verbal behavior plays an important role in gambling • The word “faster” or “slower” were never mentioned, functions were acquired through clicking rate only